Artificial neural network modeling & control for pressurized head box of paper machine

A dynamic model for pressurized head box of high speed paper machine is considered. Analysis procedures enable to anticipate the automation in the head box. An optimum, minimum control effort strategy is proposed. Simulated open and closed loop response records are computed. The simulated data has been used for training the neural network. Artificial neural network(ANN) model minimizes the interaction between physical parameters. In this paper, an ANN controller has been designed for headbox and both the controllers namely PID and ANN have been compared.